The aim of this research is to develop software for assisting prognostic assessment and selection of treatment for breast cancer patients. A parallel aim is to plan how to put the software into wide usage to allow treating physicians and women who have the disease to obtain a better estimate of outcome. The specific focus of this research is to train an artificial neural network on a data set of node-negative women who were not given chemotherapy. The neural network software will be compared with statistical techniques in its ability to estimate prognoses. Avenues of introduction and methods of testing the software will be planned. The impact of the work will be to improve the quality of medical treatment and to lower costs, due to a more precise assessment of the outcome of the disease in individual cases.